An approach to the use of packaged statistical programs for cluster,classification, and discriminant analysis of trace element data

The purpose of this paper is to present an approach to be taken when using packaged statistical programs for the evaluation of multivariate data, in particular those programs designed for clustering, classification, and discrimination purposes. A systematic step-by-step approach is outlined starting with those steps which should be conducted in order to assure that the assumptions underlying the statistical analyses are satisfied. The use of various methods and computational options in cluster, classification, and discriminant analysis is then discussed. Finally the need for an assessment of the results in view of the overall knowledge of the problem is pointed out.     

What's Next Now That the Boom in Contaminant Hydrogeology Has Busted?

This paper shows how important the historical contaminant boom, 1975 to 2005, has been to hydrogeology. Its role in this respect has never been well documented or appreciated. We use text mining and machine learning to extract information describing research trends in subsurface hydrology (SH), groundwater plus the vadose zone. The analysis, using articles from Water Resources Research (WRR) and Environmental Science and Technology, shows how SH grew from a small niche area within broader hydrologic sciences in the 1960s to become the dominant area of research by 1995. Subsequently, the performance of SH has declined, as other areas of hydrologic sciences have emerged. These patterns reflect the growth and decline of research related to contaminant topics in SH. Thus, the decline is economic—less money leads to less research. The boom in contaminant hydrogeology was effectively a 1000-year flood of money for SH. It let us outcompete the non-SH areas for a while. From 1991 to 2000, SH research in WRR was dominated by papers on contaminant-related themes. More recently, these themes and all other areas of SH except one have declined significantly in WRR. All major topics related to non-SH areas are growing except one. This evidence points to a continuing decline in competitiveness of basic research in SH. The fact that critical problems or social needs for research still exist has not changed this basic trend. The focus of research has clearly shifted away from SH to areas of hydrology associated with climate change, water cycle modeling and similar themes.     

Gas flux and carbonate occurrence at a shallow seep of thermogenic natural gas

The Coal Oil Point seep field located offshore Santa Barbara, CA, consists of dozens of named seeps, including a peripheral ～200 m² area known as Brian Seep, located in 10 m water depth. A single comprehensive survey of gas flux at Brian Seep yielded a methane release rate of ～450 moles of CH₄ per day, originating from 68 persistent gas vents and 23 intermittent vents, with gas flux among persistent vents displaying a log normal frequency distribution. A subsequent series of 33 repeat surveys conducted over a period of 6 months tracked eight persistent vents, and revealed substantial temporal variability in gas venting, with flux from each individual vent varying by more than a factor of 4. During wintertime surveys sediment was largely absent from the site, and carbonate concretions were exposed at the seafloor. The presence of the carbonates was unexpected, as the thermogenic seep gas contains 6.7% CO₂, which should act to dissolve carbonates. The average δ¹³C of the carbonates was ?29.2?±?2.8‰ VPDB, compared to a range of ?1.0 to +7.8‰ for CO₂ in the seep gas, indicating that CO₂ from the seep gas is quantitatively not as important as ¹³C-depleted bicarbonate derived from methane oxidation. Methane, with a δ¹³C of approximately ?43‰, is oxidized and the resulting inorganic carbon precipitates as high-magnesium calcite and other carbonate minerals. This finding is supported by ¹³C-depleted biomarkers typically associated with anaerobic methanotrophic archaea and their bacterial syntrophic partners in the carbonates (lipid biomarker δ¹³C ranged from ?84 to ?25‰). The inconsistency in δ¹³C between the carbonates and the seeping CO₂ was resolved by discovering pockets of gas trapped near the base of the sediment column with δ¹³C-CO₂ values ranging from ?26.9 to ?11.6‰. A mechanism of carbonate formation is proposed in which carbonates form near the sediment–bedrock interface during times of sufficient sediment coverage, in which anaerobic oxidation of methane is favored. Precipitation occurs at a sufficient distance from active venting for the molecular and isotopic composition of seep gas to be masked by the generation of carbonate alkalinity from anaerobic methane oxidation.

Compositional variability and air-sea flux of ethane and propane in the plume of a large, marine seep field near Coal Oil Point, CA

Large quantities of methane (C1), ethane (C2), and propane (C3) emanate from shallow marine seeps near Coal Oil Point (COP), California. Concentrations of these gases were analyzed in the surface water down-current of the seep field over a 15-month period. The variable proportions of C1, C2, and C3 analyzed in gas bubbles emitted from 16 distinct seeps in the COP field encompass much of the variability found in the surface waters down-current. However, waters with disproportionate levels of C1 suggest the presence of additional C1 sources. Based on three spatial surveys, covering areas up to 280 km², C2 and C3 air-sea fluxes were estimated to be in the order of 3.7 and 1.4 μmol day^?1 m^?2, respectively. Only 0.6% of C2 and 0.5% of C3 in the dissolved plume originating from the COP seep field are transferred to the atmosphere in the study area, with the fate of the remainder uncertain.     

Fine particle transport dynamics in response to wood additions in a small agricultural stream

Wood additions to streams can slow water velocities and provide depositional areas for bacteria and fine particles (e.g., particulate organic carbon and nutrients sorbed to fine sediment), therefore increasing solute and particle residence times. Thus, wood additions are thought to create biogeochemical hotspots in streams. Added wood is expected to enhance in-stream heterogeneity, result in more complex flow paths, increase natural retention of fine particles and alter the geomorphic characteristics of the stream reach. Our aim was to directly measure the impact of wood additions on fine particle transport and retention processes. We conducted conservative solute and fluorescent fine particle tracer injection studies in a small agricultural stream in the Whatawhata catchment, North Island of New Zealand in two reaches—a control reach and a reach restored 1-year earlier by means of wood additions. Fine particles were quantified in surface water to assess reach-scale (channel thalweg) and habitat-scale (near wood) transport and retention. Following the injection, habitat-scale measurements were taken in biofilms on cobbles and by stirring streambed sediment to measure fine particles available for resuspension. Tracer injection results showed that fine particle retention was greater in the restored compared to the control reach, with increased habitat-scale particle counts and reach-scale particle retention. Particle deposition was positively correlated with cobble biofilm biomass. We also found that the addition of wood enhanced hydraulic complexity and increased the retention of solute and fine particles near the wood, especially near a channel spanning log. Furthermore, particles were more easily remobilized from the control reach. The mean particle size remobilized after stirring the sediments was ~5 μm, a similar size to both fine particulate organic matter and many microorganisms. These results demonstrate that particles in this size range are dynamic and more likely to remobilize and transport further downstream during bed mobilization events.     

LANDSAT Sub-pixel Analysis in Mapping Impact of Climatic Variability on Prairie Pothole Changes

The Prairie Pothole Region in the United States contains millions of seasonal, semi-permanent, or permanent lakes and wetlands that typically range in size from 0.1 to 10 ha. These lakes and wetlands are vulnerable to climate change, especially in our study area in South Dakota, in which a period of deluge following a sharp drought considerably expanded the areal extent of prairie pothole lakes during the last decade of the twentieth century. Preliminary estimates of lake areas, determined using LANDSAT 5 and 7 images, had appreciable errors especially for the smallest of these lakes. This article describes a new sub-pixel approach integrated with a CART (Classification and Regression Tree) model using a GIS (Geographical Information System) to quantify mixed water pixels along lake boundaries to improve area estimations for pothole lakes. Errors in estimated area were typically 10% or less for lakes greater than 1 ha in size. An analysis of lakes in our study area demonstrates how lake area changed with the transition from drought to deluge. Small lakes exhibited a distinct seasonal variation in contrast to large lakes that tended to follow precipitation trends more broadly. The total water area of lakes is consistent with broad variation in rainfall.     

Multi-criteria spatial screening and uncertainty analysis applied to direct-use geothermal projects

ABSTRACT

The focus of this work is general methods for prioritization or screening of project sites based on the favorability of multiple spatial criteria. We present a threshold-based transformation of each underlying spatial favorability factor into a continuous scale with a common favorability interpretation across all criteria. We compare several methods of computing site favorability and propagating uncertainty from the data to the favorability metrics. Including uncertainty allows decision makers to determine if seeming differences among sites are significant. We address uncertainty using Taylor series approximations and analytical distributions, which are compared to computationally intensive Monte Carlo simulations. Our methods are applied to siting direct-use geothermal energy projects in the Appalachian Basin, where our knowledge about any particular site is limited, yet sufficient data exist to estimate favorability. We consider four factors that contribute to site favorability: the thermal resource described by the depth to 80°C rock, natural reservoir productivity described by rock permeability and thickness, potential for induced seismicity, and the estimated cost of surface infrastructure for heat distribution. Those factors are combined in three ways. We develop favorability uncertainty propagation and sensitivity analysis methods. All methods are general and can be applied to other multi-criteria spatial screening problems.     

Mapping Wildfire Burn Severity in Southern California Forests and Shrublands Using Enhanced Thematic Mapper Imagery

Abstract

Wildfire is a major disturbance agent in Mediterranean Type Ecosystems (MTEs). Providing reliable, quantitative information on the area of burns and the level of damage caused is therefore important both for guiding resource management and global change monitoring. Previous studies have successfully mapped burn severity using remote sensing, but reliable accuracy has yet to be gained using standard methods over different vegetation types. The objective of this research was to classify burn severity across several vegetation types using Landsat ETM imagery in two areas affected by wildfire in southern California in June 1999. Spectral mixture analysis (SMA) using four reference endmembers (vegetation, soil, shade, non‐photosynthetic vegetation) and a single (charcoal‐ash) image endmember were used to enhance imagery prior to burn severity classification using decision trees. SMA provided a robust technique for enhancing fire‐affected areas due to its ability to extract sub‐pixel information and minimize the effects of topography on single date satellite data. Overall kappa classification accuracy results were high (0.71 and 0.85, respectively) for the burned areas, using five canopy consumption classes. Individual severity class accuracies ranged from 0.5 to 0.94.     

Working in a Landscape of Recession and Expansion: Academic Jobs in Geography in the United States, 1990–2011

The recent economic recession brought much university hiring to a standstill in the United States. Geography, in spite of strong prerecession growth, was no exception. Without a sense of how the academic geography job market has changed over the past decades, however, it is difficult to assess any recession-related decline or the relative strength of any recovery. This article presents an analysis of academic job postings in the field of geography from 1990 through 2011. Using data aggregated from the AAG Newsletter, which acts as an informal clearinghouse for most academic openings for geographers at four-year colleges and universities in the United States, we assess changes in the overall magnitude in numbers of academic job openings, with the particular goal of placing the recession-based paucity of openings within its broader historical context. Our results indicate that, indeed, the recession led to a very sharp decline in advertisements, but compared to previous recessions, the recovery appears to have occurred very quickly. Open-rank and temporary/non-tenure-track positions appear to have been fairly robust to the poor economic conditions, whereas assistant professor openings were particularly hard hit.     

A method for discovery and analysis of temporal patterns in complex event data

Pattern analysis techniques currently common within geography tend to focus either on characterizing patterns of spatial and/or temporal recurrence of a single event type (e.g., incidence of flu cases) or on comparing sequences of a limited number of event types where relationships between events are already represented in the data (e.g., movement patterns). The availability of large amounts of multivariate spatiotemporal data, however, requires new methods for pattern analysis. Here, we present a technique for finding associations among many different event types where the associations among these varying event types are not explicitly represented in the data or known in advance. This pattern discovery method, known as T-pattern analysis, was first developed within the field of psychology for the purpose of finding patterns in personal interactions. We have adapted and extended the T-pattern method to take the unique characteristics of geographic data into account and implemented it within a geovisualization toolkit for an integrated computational-geovisual environment we call STempo. To demonstrate how T-pattern analysis can be employed in geographic research for discovering patterns in complex spatiotemporal data, we describe a case study featuring events from news reports about Yemen during the Arab Spring of 2011–2012. Using supplementary data from the Global Database of Events, Language, and Tone, we briefly summarize and reference a separate validation study, then evaluate the scalability of the T-pattern approach. We conclude with ideas for further extensions of the T-pattern technique to increase its utility for spatiotemporal analysis.